The size of personal data content has been consistently increasing, which can often lead to problems for vehicle automatic speech recognition (ASR) systems. Currently, content for vehicle ASR systems may be loaded based on non-specific or generic criteria, such as alphabetical order, until the storage limit of the system memory is reached. Even if it may be possible to load all of the content, it may not be desirable to load all of the content, because if a majority of the content will not be requested, the system performance might be negatively impacted. If the size of the personal data is too voluminous to be loaded and made fully accessible by the ASR system, user commands might not be understood, as speech recognition accuracy often decreases with increasing amounts of data. Thus, users may get frustrated when their requests are not understood because requested content items are randomly available as opposed to being readily available.